Electronic management of sleep related data

ABSTRACT

A system and method electronically manages sleep related data obtained by a diagnostic device. The system and method may include collecting sleep data from a patient using a diagnostic device. The sleep data may be stored in a sleep data file and delineated as multiple sleep sessions. A user may access the stored sleep data by selecting a particular sleep session. The sleep data for the selected sleep session may then be extracted from the sleep data file and presented to the user as a combination of image tiles, JavaScript elements, and an event indicator.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application is a national phase entry under 35 U.S.C. § 371of International Application No. PCT/AU2014/050305, filed Oct. 24, 2014,which claims priority from Australian Provisional Application No.2013904136, filed on Oct. 25, 2013, all of which are hereby incorporatedherein by reference.

FIELD OF THE INVENTION

The present technology relates to the detection and diagnosis ofsleep-disordered breathing. In particular, the present technologyrelates to a system for the electronic management of sleep data, such assleep related diagnostic data.

BACKGROUND OF THE TECHNOLOGY

Testing is a vital part of diagnosing patients with sleep-disorderedbreathing (SDB) and prescribing them for therapy on Home MedicalEquipment (HME). While the diagnostic testing is traditionally performedin a sleep lab, due to its convenience and cost effectiveness, homesleep testing (HST) is rapidly becoming a dominant method of diagnosingpatients with obstructive sleep apnea (OSA). It is possible that thenewly emerging home-focused diagnostic testing in time may replace alarge proportion of tradition sleep lab testing.

Thus, diagnostic providers are increasingly using portable take hometesting devices to diagnose patients with SDB. For example, patientssuffering from sleep apnea may undergo various degrees of testing byusing a devices such as the ResMed's ApneaLink® or CleveMed's SleepViewhome testing device. Such testing and diagnostic devices may generatesleep related data that may include one or more signal channels such asrespiratory flow, respiratory pressure, respiratory ventilation,respiratory effort, oxygenation, pulse, snore etc.

The data collected by the diagnostic device may then be reviewed by aSleep Lab physician. If some form of SDB condition is diagnosed, forexample OSA, the patient may be prescribed a therapy device, such as acontinuous positive airway pressure (“CPAP”) device, for homerespiratory therapy.

The patient's data associated with the use of the diagnostic device isuploaded to the service provider's servers. The only way for a treatingphysician or sleep clinician to review such data is by downloading it totheir own computer, which is typically remote to the servers. Such anupload may be associated with substantial amount of time. In practice,when reviewing patient data the download of a sleep data file alone maytake several minutes. This is because HST software solutions currentlyin the market download the entire sleep study file (e.g., an EDF+ typefile) to the user's computer, before allowing any sections of the datato be viewed. The file often includes the sleep related data fromseveral nights, with each night of sleep data itself often having anumber of sleep sessions. Thus, the size of data file associated with anentire sleep test can be significant. As a result, downloading the datafile on a personal computer often results in a waiting time of more than3 minutes before a sleep physician may begin viewing and analysing thestudy.

The above issue is further complicated when there is a need to introducesome manual changes in the diagnostic evaluation of the sleep data. Asit will be described below, sleep physicians can choose to re-evaluatediagnosed SDB events scored in the originally downloaded data file.Currently, such a change necessitates the entire amended data file to beuploaded back to the server for re-evaluation of the total sleep score.Such multiple data transfers of large sleep data files can causeunnecessary distraction and waste of time.

BRIEF SUMMARY

Aspects of the disclosure set forth a method for electronic managementof sleep related information obtained by a sleep related measurementdevice. The method may include receiving sleep data; storing the sleepdata so as to associate the sleep data with a plurality of sleepsessions; enabling a user to select for download a selected sleepsession; generating a plurality of image tiles corresponding to thesleep data of the selected session; and transmitting the plurality ofimage tiles.

In addition, the plurality of image tiles may be transmitted so that atleast a first image tile, from the plurality of image tiles, may bedownloaded by a receiving computer, prior to all of the plurality ofimage tiles being downloaded. The method may also include automaticallyscoring diagnostic events based on the received sleep data. Transmittingthe image tiles may include an event indicator that displays the scoreddiagnostic events associated with the selected sleep session, whereineach of the transmitted tiles corresponds to a time period included onthe event indicator.

In accordance with another aspect, the method may include generating areport based on the sleep data and/or the scored diagnostic events. Oneor more script elements indicative of scored diagnostic events may alsobe transmitted, with one or more script elements being manuallyadjustable by the user. One or more script elements may be superimposedonto a respective one of the plurality of image tiles when displayed toa user.

In yet another aspect, the method may include receiving data indicativeof user adjustments to one or more script elements. The automaticscoring may then be recalculated based on the received data indicativeof the user adjustments to the one or more script elements.

In still another aspect, the methods described herein may be performedby a system of one or more computing devices. The one or more computingdevices may one or more processors configured to perform the disclosedmethods.

BRIEF DESCRIPTION OF DRAWINGS

The accompanying drawings facilitate an understanding of the variousembodiments of this present technology. In such drawings:

FIG. 1 depicts a diagnostic device in accordance with aspects of thedisclosed technology;

FIG. 2 depicts a diagnostic device in accordance with aspects of thedisclosure technology;

FIG. 3 depicts schematic representation of an electronic system forfacilitating the method for electronic management of sleep related datain accordance with an aspect of the disclosed technology;

FIG. 4 depicts a visual representation of a patient's sleep related dataprovided to a user on a screen of the User's electronic device inaccordance with an aspect of the disclosed technology;

FIG. 5 depicts a schematic representation of selected functionalities ofa method for electronic management of sleep related data in accordancewith an aspect of the disclosed technology;

FIG. 6 depicts a diagnostics report provided as a result of automaticscoring of sleep related events as indicated in FIG. 4, in accordancewith an aspect of the disclosed technology;

FIG. 7 depicts the visual representation of FIG. 4, wherein theautomatically generated marking of some sleep related events has beenedited by the user;

FIG. 8 depicts a diagnostics report provided as a result of scoring ofthe edited sleep related events as indicated in FIG. 4, in accordancewith an aspect of the disclosed technology;

FIG. 9 is a flow diagram that may be performed in accordance withaspects of the disclosed technology.

DETAILED DESCRIPTION

The proposed technology utilizes a unique combination of streamingserver-side tiling technology and optimized user interface design toallow sleep related data file to be loaded onto an electronic device asa series of images. Details of some aspects of streaming server-sidetiling technology can be found in published patent documents U.S. Pat.Nos. 8,560,600 and 8,260,006. In particular, U.S. Pat. No. 8,560,600describes details of the mechanics of a server using server data torender visual map elements such as image tiles for display of maps. U.S.Pat. No. 8,260,006 describes how mapping tiles can be linked togetherseamlessly to form a single display within the user's browser.

FIGS. 1 and 2 show an example diagnostic device 101 that may be used bya patient to collect sleep related diagnostic data. The patient may weardiagnostic device 101 by strapping belt 1002 around his or her chest.Cannula 1004 may then be placed with respect to one or more of thepatient's airway passages, such as the nasal passages, so as to measureparameters associated with the patient's breathing, such as airflow.Diagnostic device 101 may also include an oximeter sensor 1006 that maymeasure the patient's pulse and oximetry levels. Oximeter sensor 1006may be worn by the patient as a finger clip. In addition, diagnosticdevice 101 may include an effort sensor 1008 for measuring patient'sbreathing effort during sleep. Effort sensor 1008 may be attached tobelt 1002 in proximity to the patient's rib cage and lungs.

As shown in FIG. 2, diagnostic device 101 may include indicator lights1010, 1011, and 1012 to indicate whether diagnostic device 101 isproperly connected to cannula 1004, oximeter sensor 1006, and effortsensor 1008, respectively. For example, indicator lights 1010-12 mayactivate, flash, or change color if diagnostic device 101 determinesthat one of the sensors are not properly connected. Testing light 1014may indicate whether a diagnostic test has been properly completed orwhether an error has occurred during the diagnostic test. Diagnosticdevice 101 may also include user interfaces, such as power button 1016.The user interface may include an interactive display (not shown) fordisplaying diagnostic data and receiving user input. As discussed below,diagnostic device 101 may collect sleep test data from the patient as heor she sleeps. This data may be stored by diagnostic device 101 andtransmitted to a remote computing device.

FIG. 3 shows an electronic system that may be implemented in connectionwith the present technology. As shown in FIG. 3, a system 100 includes apatient diagnostic device 101, a diagnostic provider (e.g., sleep lab)computer 104, a therapy device 105 (e.g., an RPT device), a therapyprovider computer 102, and a server 201, all of which may be connectedto a network 150 (the ‘cloud’). The diagnostic device 101, the computingdevice 104 (also referred to as user's computer) and the server 201(also referred to as service provider's server) may be located remotelywith respect to each other. The diagnostic device 101 may be any homesleep testing device used by a patient. As the patient uses medicaldiagnostic device 101, diagnostic data 111 may be recorded on a storagemedium, also referred to as memory 112. Diagnostic data 111 may includeany data relating to the patient's sleep test, such as date, time, andduration of test, as well as biometric clinical information such asrecorded respiratory flow data, respiratory effort data, oximetry, andpulse data. Memory 112 may be of any non-transitory type capable ofstoring information accessible by a processor, including acomputer-readable medium, or other medium that stores data that may beread with the aid of an electronic device, such as a hard-drive, memorycard, ROM, RAM, DVD or other optical disks, as well as otherwrite-capable and read-only memories.

Server 201 may include a processor 210 and a memory 220. Memory 220 isused for storing data 230, which are accessible by processor 210, aswell as instructions 234, which may be executable or otherwise usable bythe processor 210. The memory 220 may be of any non-transitory typecapable of storing information accessible by the processor, including acomputer-readable medium, or other medium that stores data that may beread with the aid of an electronic device, such as a hard-drive, memorycard, ROM, RAM, DVD or other optical disks, as well as otherwrite-capable and read-only memories. Systems and methods may includedifferent combinations of the foregoing, whereby different portions ofthe instructions and data are stored on different types of media.

The instructions 234 may be any set of instructions to be executeddirectly (such as machine code) or indirectly (such as scripts) by theprocessor. For example, the instructions may be stored as computer codeon the computer-readable medium. In that regard, the terms“instructions” and “programs” may be used interchangeably herein. Theinstructions may be stored in object code format for direct processingby the processor, or in any other computer language including scripts orcollections of independent source code modules that are interpreted ondemand or compiled in advance. Functions, methods and routines of theinstructions are explained in more detail below. Instructions 234 mayalso contain instructions for operating one or more virtual servers,such as Communication (Comm) server 240, Easy Care Online (ECO) Server250, and Communication Abstraction Layer (CAL) server 260.

The Communication Abstraction Layer (CAL) is responsible forcommunicating with Therapy Devices. The CAL's core responsibilitiesinclude, obtaining daily summary data for active patients; retrievingand changing therapy device settings; and converting raw therapy devicedata into an easily digestible format.

The Communications Server (Comm) is responsible for initiallycommunicating with the wireless Therapy Devices and validating theiroutput. The Communications Server's core responsibilities includes,communicating with Flow Generators via a Communication Module or inbuiltCommunications Device; validating the incoming wireless data; andconverting the wireless data into a format which can be read by the CALserver.

The ECO Server is responsible for application functionality within thesystem. The ECO Server's core responsibilities include presentingpatient and device information within the user interface, writing andmanaging patient health information and running applications related tothe technology. This is the server directly responsible for running theapplications associated with the proposed tiling technology.

The data 230 may be retrieved, stored and/or modified by processor 210in accordance with the instructions 234. For instance, although thesystem and method is not limited by any particular data structure, thedata may be stored in computer registers, in a relational database as atable having a plurality of different fields and records, XML documentsor flat files. The data may also be formatted in any computer-readableformat. The data may comprise any information sufficient to identify therelevant information, such as numbers, descriptive text, proprietarycodes, references to data stored in other areas of the same memory ordifferent memories (including other network locations) or informationthat is used by a function to calculate the relevant data. Data 230 mayinclude one or more databases, including a Comm database 231, CALdatabase 232, ECO database 233, and HST database 235.

The processor 210 may be any conventional processor, includingcommercially available processors. Alternatively, the processor may be adedicated device such as an application specific integrated chip (ASIC)or field-programmable gate array (FPGA), for example. Although FIG. 3functionally illustrates the processor, memory, and other elements ofserver 201 as being within the same block, it will be understood bythose of ordinary skill in the art that the processor and memory mayactually comprise multiple processors and memories that may or may notbe stored within the same physical housing. For example, memory may be ahard drive or other storage media located in a housing different fromthat of server 201. Accordingly, references to a processor or computerwill be understood to include references to a collection of processorsor computers or memories that may or may not operate in parallel or evenbe located at the same site. Rather than using a single processor toperform the steps described herein some of the components such assteering components and deceleration components may each have their ownprocessor that only performs calculations related to the component'sspecific function. Thus, server 201 may be referred to as both a systemand an apparatus.

Computers 102, 103 and 104 may include all of the components normallyused in connection with a computer, such as a central processing unit(CPU), memory (e.g., RAM and internal hard drives) storing data 120 and121, instructions 130 and 131 such as a web browser, an electronicdisplay 110 and 116 (e.g., a monitor having a screen, a small LCDtouch-screen or any other electrical device that is operable to displayinformation), and user input 160 and 161 (e.g., a mouse, keyboard, touchscreen, and/or microphone).

The memory 112 may be internal to the diagnostic device 101 and may beaccessed by connecting an USB data cable to a separate computer.Accordingly, the term “diagnostic device” in such a case may beinterpreted broadly to include a personal computer, such as a desktop ormobile computer, which contains diagnostic data 111 collected from amedical device, such as a home sleep testing device. In addition, whileFIG. 3 illustrates server 201 and devices 101-104 as being connected viaa common network 150, each two or more devices within system 100 may beconnected via a separate network.

In one example, ECO server 250 and ECO database 233 may reside on adevice at a location that is remote from Comm server 240, Comm database231, CAL server 260, and CAL database 232. In addition, Comm server 240,Comm database 231, CAL server 260, and CAL database 232 may exist on asingle device.

A patient may use a medical diagnostic device 101 in connection with adiagnostic order prescribed by a primary care physician/general medicalpractitioner or by a sleep physician. As the patient uses the device,diagnostic device 101 may collect data including physiological clinicalinformation, time and dates of usage, and any other relevant data. Inthis regard, although FIG. 1 illustrates a specialized diagnostic devicethat does not provide treatment or therapy, in some cases, a diagnosticdevice may also be capable of providing a therapy. Such an examplediagnostic device may be a respiratory pressure therapy device, such aCPAP device, which is provided with diagnostic capabilities.

A user of system 100, such as a user of computer 104, may have a directaccess to memory 112 of the medical diagnostic device 101.Alternatively, the user can connect diagnostic device 101, such as via aUSB cable, to a local computer, which may then upload the data to theserver 201, or may allow the computer 104 to access the data of internalmemory 112. A web browser 131 on the computer 104 may then be used tocontact server 201 and upload diagnostic data 111 to one or more of theserver's databases. Alternatively, the diagnostic device 101 may includea Bluetooth or Wi-Fi transmission capabilities and the diagnostic datamay be uploaded directly from the diagnostic device 101 to the server201 wirelessly.

The diagnostic data 111 provided to server 201 from diagnostic device101 may be stored in the HST database 235. For example, each diagnosticdevice 101 may be assigned a device ID, which is provided to server 201along with the diagnostic data. The diagnostic data may then be storedby server 201 in a database that uses the device ID to associate thereceived data with the appropriate patient diagnostic device 101.

In some instances, a patient is required to use a medical diagnosticdevice for a set duration and exhibit certain clinical symptoms in orderto be eligible to qualify for therapy. For example, a patient who hasbeen ordered a home sleep test will often be required to use thediagnostic device for at least four hours and exhibit an Apnea-HypopneaIndex (AHI) of greater than 5 in order for a physician to write aprescription for CPAP therapy. System 100 may then be used to trackwhether the patient has been compliant in using the diagnostic deviceand may assist a physician in making a diagnosis.

A sleep data file covering one or more sleep sessions may be uploadedfrom a diagnostic device 101 to a remote server, such as by beinguploaded to the HST database of server 201 shown in FIG. 3. The sleepdata file may be in an EDF+ format and may include built-in delineatorsthat indicate the beginning and the end of sleep sessions within thefile. An individual sleep session may be defined by a predetermined timeperiod or a predetermined set of testing conditions. In particular, asleep session may correspond to the time period in which the patient hasexperienced a period of continuous or near-continuous sleep. Forexample, if the patient slept uninterruptedly from 12:15 AM to 7:30 AM,that period of time may be defined as a single sleep session. A sleepsession may also be based on some predetermined period of time in whichsleep data was collected. For example, a sleep session may be defined bya four-hour period of time in which sleep data was collected.

The delineators within the sleep data file allow for the identificationof separate sleep sessions, as well as for the selection and extractionof a specific session for download. The sleep data may include aplurality of separate data channels corresponding to the variousdiagnostic sensor data collected by diagnostic device 101. For example,a sleep data file may include data from five separate data channelscorresponding to measurements of the patient's air flow, respiratoryeffort, oxygen saturation, pulse, and snoring.

When the sleep data is uploaded onto the server 201, a software analysermay run at the server to autoscore predefined events, such as SDB events(e.g., apnea, hypopnea), oxygen desaturation events, etc. The scoringcomprises associating specific sleep data, such as flow or oxygendesaturation data, with specific sleep events, such as apnea, hypopnea,etc. The scoring is based on predetermined algorithms programmed in theanalyser. The analyser may also generate a report, such as the one thatwill be discussed later in the text in relation to FIG. 6. The reportmay include a statistical summary of the data itself and/or of eventsscored on the basis of the uploaded data. The report of a specific sleepsession may be displayed to the user when a session is selected. Thereport for the largest sleep session for a given night may also bedisplayed as a default report for the respective date, assuming that theuser will be most interested in this session.

A sleep session may be selected in many ways. In one example, a user(e.g., a Sleep Lab Physician) may choose a date and view the availablesleep sessions for that date. He or she may then choose a sleep sessionfor that date based on one or more criteria, such as the duration of theavailable sessions. For example, the user may choose the longest sessionfor a particular period of time. When a particular session is selectedfor download, say at a Sleep Lab Physician's computer 104, the server201 may read the selected session data from the sleep study file andconvert the data from the five signal channels into a series of bitmapimage files (tiles), which the user's browser downloads. Whilst theoriginal data may be in an EDF+ format, these tiles can be in any one ofvarious image formats, such as GIF, BMP, PNG, etc. The download of theimages is typically in a time-lapse sequence from left to right.However, this does not have to be the case and in the general case theimages may be downloaded in any order. Each image that is to bedisplayed to the user is based on data from the sleep file, as well asadditional markers of identified SDB events (also referred to in thisspecification as diagnostic events). Markers for other events that adata analyser at the server has been configured to score automaticallybased on the provided sleep data, may also be included in the displayedimage. Each image corresponds to a predetermined length of time andtogether the combined images represent the entire selected session.

If the user selects a sleep session of, for example, five hours oflength within a file for review, the session may be rendered into thirty10-minute long images, also referred to as image tiles, eachrepresenting a sequential part of the session. The time represented byeach of these images may vary. For example, the images may vary between1 minute or less to 1 hour or more. A default image time period between5 and 30 minutes may be set for certain forms of data review. A webbrowser at the user electronic device, such as computing device 104 inFIG. 3, may compile what is displayed on the user electronic deviceinterface from a number of image elements downloaded from server 201.One or more HTML files, corresponding to at least some of the imagetiles, may also be generated at the server 201 based on the originalsleep data. The one or more HTML files include scripts, such as Javascripts, indicative of any SDB events requiring highlighting on thesignal channels.

A special signal bitmap image tile may be generated at server 201 on thebasis of the information for the entire session. This tile may be usedto visualise a time line that corresponds to a time period covered bythe downloaded tiles. Thus, one or more of the remaining tiles maycorrespond to a time period included on this tile. This specific imagetile may include visualisation of one or more channels of signal data,as well as an indication of various SDB events through the session. Thetile may be referred to as an event indicator. The event indicator maybe downloaded to computing device 104 simultaneously with the datachannel image tiles. As the event indicator may be the first tile to bedownloaded, it can be clicked on by the user to adjust the view/displayto specific points of interest within the displayed session. This allowsthe user to view specific sections of the data with increasedresolution, effectively providing a zoomed view of the respectivesection.

An example screenshot 400 of a diagnostic session that may be displayedto the user can be seen in FIG. 4. Screenshot 400 displays a combinationof a single image tile 10, an event indicator 20, and varioussuperimposed JavaScript elements 30. The image tile 10 includesdepictions 12 for five separate data channels, which correspond tomeasurements of the patient's air flow, patient's respiratory effort,oxygen saturation, pulse and snore. Data channel depictions 12 are basedon the underlying diagnostic data that was collected by diagnosticdevice 101. JavaScript elements 30 are indications of SDB events thatmay have been identified automatically at the server 201 based onprocessing of the received sleep data from the one or more diagnosticchannels. The identification of such SDB events may also be referred toas scoring. The elements 30 are displayed by the browser at the user'scomputing device 104 on the basis of scripts included in the HTML filedownloaded together with the image tiles. Elements 30 may besuperimposed onto a respective image tile 10 so as to indicate when apotentially significant SDB event has occurred in connection with adisplayed one or more data channels. For example, JavaScript elements 30have been superimposed onto the data channel depictions 12 of thepatient's air flow and respiratory effort, so as to identify events 30of central and obstructive sleep apnea. Similarly, as shown in FIG. 4,JavaScript elements 30 have been superimposed onto the patient'soximetry data so as to indicate events of oxygen desaturation. It isnoted that although elements 30 are described as JavaScript elements,other scripting or processor control elements may be implemented inaddition to, or as an alternative to JavaScript in some versions of thepresent technology. Such alternatives may include HTML5 protocol,cascading style sheets (CSS), etc.

The top of screenshot 400 displays event indicator 20, which isassociated with the entire sleep session. In the illustrated example thesleep session spans from 10:37 pm to 06:08 am. The event indicator 20may also identify instances of scored SDB events that have occurredduring the sleep session. In particular, box 21 may identify when SDB,such as central sleep apnea, has occurred.

As seen in FIG. 4, screenshot 400 displays an event indicator 20 of asession that corresponds to a time period between 10:37 PM and 6:08 AM.This time period may be treated by the disclosed system as a singlesession or as part of a session. A user viewing screenshot 400 mayselect a portion of event indicator 20 to view a particular time periodwithin the session. One or more image tiles corresponding to theselected time period may then be displayed to the user. For example,screenshot 400 shows an image tile 10 that corresponds to a time periodbetween 1:11 AM and 1:14 AM. The relative location of the displayed tilein relation to the entire sleep session may be shown on the eventindicator, as indicated by frame 701 located within the event indicatorbar in FIG. 7. In this way, event indicator 20 may be used to show asummary of the patient's sleep session, while allowing a user to alsoquickly navigate to one or more time periods within the session, so asto view detailed data in connection with one or more data channels.Event indicator 20 may also display data relating to the patient's sleepsession. For example, event indicator 20 of FIG. 4 shows oxygensaturation data 50. When viewing a particular sleep session, the dataincluded in event indicator 20 may be the only data set preloaded ontothe user's display so as to always be viewed in its entirety.

FIG. 5 shows how the event indicator 20, image tiles 10 and JavaScriptelements 30 may be combined by the disclosed system to produce thewebpage shown in screenshot 400. As described above, the event indicator20 and image tiles 10 will correspond to a sleep session that has beenselected by a user. A particular period of time within event indicator20 may then be selected by the user, for which a corresponding one ormore image tiles 10 and corresponding JavaScript elements 30 areselected and combined to generate the displayed webpage. In particular,once an image tile 10 is downloaded onto computing device 104, theprocessor of computing device 104 may read an associated HTML file anddetect if there are any marked SDB events requiring highlighting on thesignal channels. If such an event is identified, and it falls within thetime interval being currently displayed on the web browser, theprocessor may prompt the web browser to render JavaScript elements 30 ina that is displayed above the image tiles, as shown in FIG. 5. As a usermoves through the images of the session, the processor updates thecomputing device display 116 to render more JavaScript elementsaccording to which part of the study is being viewed and may unloadelements which are no longer being viewed, so as to maintain efficientuse of the computing device's memory.

The manner in which the sleep related data file is downloaded fromserver 201 to computing device 104 allows for efficient time and datamanagement when reviewing the data file. In particular, the disclosedsystem does not require an entire data file to be downloaded, thusreducing substantially the sleep physician's download time. With theproposed technology, large sleep data files may be transferred to theECO server 250 well in advance of the time when the user attempts toaccess them. The much smaller image tiles 10 may be generated on demand,based on a selected sleep session data that is read from the sleep datafile. The fact that the images tiles are generally substantially smallerin size than the original data and that the download is executed onetile at a time, facilitates much shorter download times (typically lessthan 10-30 seconds). The user may start reviewing study datasubstantially instantaneously, once the first image tile 10 isdownloaded. Furthermore, after the download of the event indicator,which may be transmitted to be the first downloaded tile, the user isable to immediately select a time slot of interest. Once the user haschosen a particular time of interest, the respective one or more imagetiles may be immediately and preferentially downloaded, allowing theuser to start reviewing the time slot of interest substantiallyinstantaneously.

As was discussed above, SDB events may be autoscored at the server 201.Based on the raw sleep data and/or the scored sleep events, an analyserat the server 201 may also generate a report, shown by screenshot 600 inFIG. 6. This specific report may include a statistical summary ofvarious measured parameters, such as pulse, breaths, oxygendesaturation, Apnea and Hypopnea indices. Summary of the autoscoredevents, such as Apneas (6), hypopneas (2), oxygen desaturation events(6) etc. may also be displayed. This type of patient's sleep diagnosticstatistics may be displayed to a user of computing device 104. A totaldiagnostic score, which in this case is represented by theApnea-Hypopnea Index 602, is automatically calculated (scored), based onthe SDB diagnostic events automatically scored by the analyzer for therespective one or more sleep sessions. The AHI 602 is in this case 1.2,indicating that the patient has not suffered from SDB.

A sleep session may also be manually scored directly from the browserthat is running on computing device 104. The manual scoring may beperformed by a user of computing device 104 adjusting the size andnumber of JavaScript elements 30 displayed within one or more imagetiles 10. For example, FIG. 7 shows screenshot 700 in which a user isadding JavaScript element 30′ to image tile 10. The addition ofJavaScript element 30′ may be performed by the user selecting aparticular point along one or more of the data channel depictions 12using a cursor and then dragging the cursor along the selected channeldepiction 12 so that the generated JavaScript element 30′ corresponds tothe desired period of time. A user may also select existing JavaScriptelements so that they may be reshaped or deleted by the user. In thisway, the user may perform a re-evaluation of the patient's auto-score.Upon completion of the re-evaluation, the patient's diagnosticstatistics may be re-calculated based on the modified placement of theJavaScript elements 30.

For example, as was mentioned above, an AHI auto-score of 1.2 wascalculated in the report shown in FIG. 6, indicating a negativediagnosis for OSA. However, upon reviewing the raw data illustrated bythe different channel signals, a sleep physician user may decide tooverride the auto-score manually by introducing changes to theautoscored diagnostic events, as shown in FIG. 7.

Once satisfied with the accuracy of the identified SDB events, the usermay save the amended session and data indicative of the introducedchanges may be sent from computing device 104 to server 201. The server201 may recalculate the patient's diagnostic statistics based on themanual amendments introduced to the java script elements 30. As can beseen in FIG. 8, the report statistics have been updated according to themanually adjusted diagnostic events. The patient's manually adjusted SDBscore (the AHI score 802) has been recalculated to be 29.9. Thismanually adjusted AHI score 802 now indicates that the patient has OSA.Thus, a qualified clinician may choose to override the auto-scorealgorithm to affect the outcome of the diagnosis. Based on the manualscores and the recalculated total SDB score, a new updated report may begenerated and provided to the user's browser so as to be presented tothe user.

FIG. 9 shows flow diagram 900 of a process associated with the describedtechnology. Portions of the process may be performed by various parts ofsystem 100 of FIG. 3, in accordance with aspects of the technology setforth above. In block 910, sleep related physiological data is receivedfrom a diagnostic device 101. The received sleep data may be diagnosticdata including one or more of the data types discussed in relation toFIGS. 1 and 2 and may be associated with one or more sleep sessions. Forexample, the sleep data may have been collected over a period of one ormore nights. In block 920, the received sleep data may be associatedwith a particular data file and stored as one or more sleep sessionsdelineated within the data file. The data may be received by anelectronic device, such as the server 201, and stored in memory, such asin the HST database 235 of memory 220.

As described above, apart from the sleep data itself, the sleep datafile may contain delineators that identify different sessions within thesleep data file. As shown in block 930, an automatic data analyzer atthe server 201 may be configured to automatically score various SDBevents identified on the basis of the received sleep related data. Suchevents then may become a part of the user's SDB statistics. For example,based on these automatically scored events, an overall SDB score may beallocated to the patient. The sleep data file, or an associated pairedfile, may include data associated with SDB event data indicatorsgenerated during the autoscoring. In block 940, a request is receivedfor sleep data that is associated with a particular sleep session. Forexample, a user of computing device 104 may request that server 201provide sleep data associated with a particular sleep data file of aparticular user, which was taken on a particular date. Based on thereceived request, the sleep data from the selected session may generateone or more image tiles (block 950). As described above, one or moreimage tiles may be generated for a single session, and each image tilemay contain data from multiple data channels. The generated image tilesare then transmitted to the requesting computing device (block 960). Thedata indicating the SDB events automatically scored within the selectedsession may also be transmitted, possibly as a script (such as Javascript) within an HTML file that is used by the browser of the receivingcomputer (e.g. computing device 104) to display the tiles. The imagetiles may be transmitted and displayed in a manner so that a user maybegin to view at computing device 104 one or more of the tilesimmediately upon the download of these specific one or more tiles, andprior to all of the image tiles being transmitted by server 201.

The requesting computing device (e.g., computer 104) may receive thetransmitted image tiles and the HTML file with the scripts indicatingautomatically scored SDB events. The computing device 104 may thendisplay both the tiles and their respective script elements indicativeof the automatically scored SDB events (block 980). The superimposedJavaScript elements are superimposed onto the image tile so as tocorrespond to locations wherein a diagnostic event has supposedlyoccurred. The identification of the diagnostic event may be based on ananalysis, by server 201, of the underlying data within the image tile.For example, based on air flow data, periods of OSA may be identified.JavaScript elements may be superimposed onto the air flow data shown inan image tile, so as to indicate the time periods in which therespective identified OSA events occurred.

The overall patient's SDB statistic and/or condition may be scored basedon the identified diagnostic events (block 970). For example, server 201may provide an AHI auto-score based on the SDB events scored during oneor more sleep sessions. As described above, the user of computing device104 may adjust the JavaScript elements that are displayed with the imagetiles (block 990). This adjustment may add, remove, or otherwise changevarious JavaScript elements. Data indicative of this manual change tothe scored SDB events may be then transferred from the user's computingdevice 104 to the server 201 (block 995). Upon receipt of the dataindicative of the adjustments to the JavaScript elements, server 201 mayrecalculate the patient's SDB score based on the received manuallyadjustments (block 970).

In the above description, it should be noted that some of the blocks,such as 910-970, may be performed at server 201, while the remainingsteps may be performed at a user electronic device, such as computingdevice 104. Also, the disclosed methods do not require that each of theblocks shown in flow diagram 900 be performed, nor must they beperformed in the order displayed. Additional blocks may also be added toflow diagram 900 in accordance with the disclosed methods.

The proposed sleep related data processing method may run nativelywithin the user's web-browser. This is beneficial to the serviceprovider, because it avoids the complications associated with of theirsoftware having to be compatible with any one of a number of client-sideapplications. For the user of computing device 104, it providessimplicity, as it avoids the need to install and maintain dedicatedsoftware. Since no third party plug-ins are required, the applicationmay also perform quickly and reliably. The application may be run notonly on PCs, but also on tablets, smart phones and other mobile devices.

An Additional problem with currently used data processing andvisualisation applications is that they are reliant on 3^(rd) partyplugins (e.g. Java applet versions) for viewing the data at the clientside. Such dependence can make their performance unpredictable, due topossible deficiencies in the third party plugins and unpredictableversion updates. Current applications are also suitable only foroperation on a PC.

In the disclosed method, the workload may be shifted from the processorof the local user's computing device onto the processors of the remoteservers, giving the local electronic device more control over the userexperience and reducing dependency on the capabilities of the client'scomputer/browser. This results in a more efficient method of datamanagement and a highly responsive user experience. The approacheffectively transforms a difficult to control problem, such as having toconsider the capabilities of client machines in dealing with highresolution browser data and variations in Java applet versions, into aproblem that can be efficiently managed, such as by processing the largesleep files using the service provider's substantial servercomputational capacity. This results in simplified testing, fasterdevelopment, and a more consistent user experience in the final product.

The improved efficiency of the technology allows efficient processing ofhigh volume sleep study data (e.g. 8 Million data points for a 10 hrstudy can be displayed in approximately 10-30 seconds).

In addition, the proposed technology, such as with processor controlinstructions, brings the following potential advantages:

The ability to display a sleep related study data natively within a webbrowser as a series of individual bitmap images.

Time efficiency—a user can start reviewing one or more of the imagessubstantially instantaneously and well before a transmission of allbitmap images being complete.

The diagnostic events are conveniently displayed via a single line studyevents bar (e.g., Event Indicator).

The ability to select for download, within a large sleep data file,individual sleep sessions of a diagnostic recording on demand (e.g., ifseveral nights of data were recorded the browser will only load thespecific selected night of data that the user has selected for viewing).

The ability to view a summary of a sleep session and to quickly navigateto specific portions of the sleep session using the presented summary.

The ability to manually edit sleep study markers using JavaScriptelements within a web browser.

The ability to resend data indicative of the change imparted to theedited elements to the cloud, where the sleep study statistic (alsoscore) is recalculated based on the changes. All of the recalculations,updates, and data transfer are much more efficient as they are performedwithout the need of downloading large sleep data files from the serverto the user's computer and without the need of uploading amended datafiles from the user's computer back to the server. In one example, onlydata indicative of the change to the SDB events indicators is sent backto the server.

A convenient visualisation of all SDB events for the entire session isprovided by way of a single line study events bar (Events Indicator).

While the disclosed technology has been described in connection withwhat are presently considered to be the most practical and preferredembodiments, it is to be understood that the invention is not to belimited to the disclosed embodiments, but on the contrary, is intendedto cover various modifications and equivalent arrangements includedwithin the spirit and scope of the disclosed technology. Also, thevarious embodiments, e.g., aspects of one embodiment may be combinedwith aspects of another embodiment to realize yet other embodiments.

For example, instead of using the user's electronic device browser todownload sleep data related image tiles generated at the remote server,an alternative method may involve reproducing both the sleep data andthe SDB event data at the user's computing device 104 by way of HTMLfiles with embedded java scripts. Such a method may utilize a thirdparty JavaScript charting library, such as “JFreeChart”, to allow forthe download of HTML and JavaScript elements to the user's electronicdevice to display the various signal channels and the clinical marketsin the device's browser.

Upon a user selecting a session to view, the server application may readthe selected session from the sleep study file (EDF+ format) and convertthe signal data and the automatically generated clinical markers into aseries of data points which are loaded into the JavaScript chartinglibrary. This library in turn converts the points to an array of HTMLand JavaScript elements which are downloaded to the user's browser anddisplayed as images. Thus, the method can be used with differentdownload mechanisms.

The method is also flexible as to the type of sleep data to which it isapplicable. While the method has been illustrated with reference tosleep data and, more specifically to specific data channels illustratedin FIGS. 4 and 7, it is to be understood that the method may be usedwith other sleep-related data. For example, data detected and/orgenerated by various contact-less sleep monitors, such as SleepMinder™or the like, can also be downloaded in similar manner. Such data mayinclude, but is not limited to, detected sleep stages, patient'stemperature, heart rate, blood pressure, breathing rate, snoring,environmental parameters, such as sound, temperature, light level etc.Accordingly, the scored events 30 may not be SDB events, as discussed inthe above description, but other type of events that are associated withthe specific type of sleep data used.

A portion of the disclosure of this patent document contains materialwhich is subject to copyright protection. The copyright owner has noobjection to the facsimile reproduction by anyone of the patent documentor the patent disclosure, as it appears in the Patent and TrademarkOffice patent file or records, but otherwise reserves all copyrightrights whatsoever.

Unless the context clearly dictates otherwise and where a range ofvalues is provided, it is understood that each intervening value, to thetenth of the unit of the lower limit, between the upper and lower limitof that range, and any other stated or intervening value in that statedrange is encompassed within the technology. The upper and lower limitsof these intervening ranges, which may be independently included in theintervening ranges, are also encompassed within the technology, subjectto any specifically excluded limit in the stated range. Where the statedrange includes one or both of the limits, ranges excluding either orboth of those included limits are also included in the technology.

Furthermore, where a value or values are stated herein as beingimplemented as part of the technology, it is understood that such valuesmay be approximated, unless otherwise stated, and such values may beutilized to any suitable significant digit to the extent that apractical technical implementation may permit or require it.

Unless defined otherwise, all technical and scientific terms used hereinhave the same meaning as commonly understood by one of ordinary skill inthe art to which this technology belongs. Although any methods andmaterials similar or equivalent to those described herein can also beused in the practice or testing of the present technology, a limitednumber of the exemplary methods and materials are described herein.

It must be noted that as used herein and in the appended claims, thesingular forms “a”, “an”, and “the” include their plural equivalents,unless the context clearly dictates otherwise.

All publications mentioned herein are incorporated by reference todisclose and describe the methods and/or materials which are the subjectof those publications. The publications discussed herein are providedsolely for their disclosure prior to the filing date of the presentapplication. Nothing herein is to be construed as an admission that thepresent technology is not entitled to antedate such publication byvirtue of prior invention. Further, the dates of publication providedmay be different from the actual publication dates, which may need to beindependently confirmed.

Moreover, in interpreting the disclosure, all terms should beinterpreted in the broadest reasonable manner consistent with thecontext. In particular, the terms “comprises” and “comprising” should beinterpreted as referring to elements, components, or steps in anon-exclusive manner, indicating that the referenced elements,components, or steps may be present, or utilized, or combined with otherelements, components, or steps that are not expressly referenced.

Although the technology herein has been described with reference toparticular embodiments, it is to be understood that these embodimentsare merely illustrative of the principles and applications of thetechnology. In some instances, the terminology and symbols may implyspecific details that are not required to practice the technology. Forexample, although the terms “first” and “second” may be used, unlessotherwise specified, they are not intended to indicate any order but maybe utilised to distinguish between distinct elements. Furthermore,although process steps in the methodologies may be described orillustrated in an order, such an ordering is not required. Those skilledin the art will recognize that such ordering may be modified and/oraspects thereof may be conducted concurrently or even synchronously. Itis therefore to be understood that numerous modifications may be made tothe illustrative embodiments and that other arrangements may be devisedwithout departing from the spirit and scope of the technology.

Also, the various embodiments described above may be implemented inconjunction with other embodiments, e.g., aspects of one embodiment maybe combined with aspects of another embodiment to realize yet otherembodiments. In addition, while the technology has particularapplication to sleep related data and diagnostic data associated withpatients suffering from OSA and other SDB, it is to be appreciated thatpatients suffering from other illnesses (e.g. congestive heart failure,morbid obesity, stoke, bariatric surgery, etc.) can derive benefit fromthe above teachings. Moreover, the above teachings have applicabilitywith patients and non-patients alike in non-medical applications.

GLOSSARY

Air: Air will be taken to include breathable gases, for example air withsupplemental oxygen.

Auto-scoring: The automated process where a custom algorithm analyzesthe sleep study's raw data and marks up/highlights areas where thealgorithm detects occurring clinically significant SDB events

Continuous Positive Airway Pressure (CPAP): CPAP treatment will be takento mean the application of a supply of air or breathable gas to theentrance to the airways at a pressure that is continuously positive withrespect to atmosphere, and preferably approximately constant through arespiratory cycle of a patient. In some forms, the pressure at theentrance to the airways will vary by a few centimeters of water within asingle respiratory cycle, for example being higher during inhalation andlower during exhalation. In some forms, the pressure at the entrance tothe airways will be slightly higher during exhalation, and slightlylower during inhalation. In some forms, the pressure will vary betweendifferent respiratory cycles of the patient, for example being increasedin response to detection of indications of partial upper airwayobstruction, and decreased in the absence of indications of partialupper airway obstruction.

European Data Format (EDF+): A standard file format designed forexchange and storage of medical time series. It is the native file whichmost diagnostic devices, including the ApneaLink, record into. The filecan contain multiple nights/sessions of sleep data as well as markers ofSDB events.

Interpretation: The process by which a Sleep Physician views resultsfrom a sleep study and makes a clinical diagnosis in regards to whethera patient requires therapy for further testing.

Manual Scoring: The process of looking at a sleep study's raw data andmanually marking up/highlighting areas where the user believessignificant SDB events are occurring to the patient.

Re-analyze/Re-calculate: The process of taking new input data generatedfrom a manual score or a change of parameters and feeding it back intoanalyzer to produce new clinical statistics, such as AHI.

Sleep physician: A physician certified by the board of the AmericanAssociation of Sleep Medicine as legally qualified to give a diagnosisfor various Sleep Disordered Breathing conditions.

Obstructive Sleep Apnea (OSA): A form of Sleep Disordered Breathing(SDB), is characterized by events including occlusion or obstruction ofthe upper air passage during sleep. It results from a combination of anabnormally small upper airway and the normal loss of muscle tone in theregion of the tongue, soft palate and posterior oropharyngeal wallduring sleep. The condition causes the affected patient to stopbreathing for periods typically of 30 to 120 seconds in duration,sometimes 200 to 300 times per night. It often causes excessive daytimesomnolence, and it may cause cardiovascular disease and brain damage.The syndrome is a common disorder, particularly in middle agedoverweight males, although a person affected may have no awareness ofthe problem. See U.S. Pat. No. 4,944,310 (Sullivan).

Cheyne-Stokes Respiration (CSR): A form of sleep disordered breathing.CSR is a disorder of a patient's respiratory controller in which thereare rhythmic alternating periods of waxing and waning ventilation knownas CSR cycles. CSR is characterised by repetitive de-oxygenation andre-oxygenation of the arterial blood. It is possible that CSR is harmfulbecause of the repetitive hypoxia. In some patients CSR is associatedwith repetitive arousal from sleep, which causes severe sleepdisruption, increased sympathetic activity, and increased afterload. SeeU.S. Pat. No. 6,532,959 (Berthon-Jones).

Obesity Hyperventilation Syndrome (OHS): The combination of severeobesity and awake chronic hypercapnia, in the absence of other knowncauses for hypoventilation. Symptoms include dyspnea, morning headacheand excessive daytime sleepiness.

Chronic Obstructive Pulmonary Disease (COPD): Encompasses any of a groupof lower airway diseases that have certain characteristics in common.These include increased resistance to air movement, extended expiratoryphase of respiration, and loss of the normal elasticity of the lung.Examples of COPD are emphysema and chronic bronchitis. COPD is caused bychronic tobacco smoking (primary risk factor), occupational exposures,air pollution and genetic factors. Symptoms include: dyspnea onexertion, chronic cough and sputum production.

Neuromuscular Disease (NMD): A term that encompasses many diseases andailments that impair the functioning of the muscles either directly viaintrinsic muscle pathology, or indirectly via nerve pathology. Some NMDpatients are characterised by progressive muscular impairment leading toloss of ambulation, being wheelchair-bound, swallowing difficulties,respiratory muscle weakness and, eventually, death from respiratoryfailure. Neuromuscular disorders can be divided into rapidly progressiveand slowly progressive: (i) Rapidly progressive disorders: Characterisedby muscle impairment that worsens over months and results in deathwithin a few years (e.g. Amyotrophic lateral sclerosis (ALS) andDuchenne muscular dystrophy (DMD) in teenagers); (ii) Variable or slowlyprogressive disorders: Characterised by muscle impairment that worsensover years and only mildly reduces life expectancy (e.g. Limb girdle,Facioscapulohumeral and Myotonic muscular dystrophy). Symptoms ofrespiratory failure in NMD include: increasing generalised weakness,dysphagia, dyspnea on exertion and at rest, fatigue, sleepiness, morningheadache, and difficulties with concentration and mood changes.

Apnea: According to some definitions, an apnea is said to have occurredwhen flow falls below a predetermined threshold for a duration, e.g. 10seconds. An obstructive apnea will be said to have occurred when,despite patient effort, some obstruction of the airway does not allowair to flow. A central apnea will be said to have occurred when an apneais detected that is due to a reduction in breathing effort, or theabsence of breathing effort, despite the airway being patent. A mixedapnea occurs when a reduction or absence of breathing effort coincideswith an obstructed airway.

Breathing rate: The rate of spontaneous respiration of a patient,usually measured in breaths per minute.

Duty cycle: The ratio of inhalation time, Ti to total breath time, Ttot.

Effort (breathing): Breathing effort will be said to be the work done bya spontaneously breathing person attempting to breathe.

Expiratory portion of a breathing cycle: The period from the start ofexpiratory flow to the start of inspiratory flow.

Flow limitation: Flow limitation will be taken to be the state ofaffairs in a patient's respiration where an increase in effort by thepatient does not give rise to a corresponding increase in flow. Whereflow limitation occurs during an inspiratory portion of the breathingcycle it may be described as inspiratory flow limitation. Where flowlimitation occurs during an expiratory portion of the breathing cycle itmay be described as expiratory flow limitation.

Hyperpnea: An increase in flow to a level higher than normal flow rate.

Flow rate: The instantaneous volume (or mass) of air delivered per unittime. While flow rate and ventilation have the same dimensions of volumeor mass per unit time, flow rate is measured over a much shorter periodof time. In some cases, a reference to flow rate will be a reference toa scalar quantity, namely a quantity having magnitude only. In othercases, a reference to flow rate will be a reference to a vectorquantity, namely a quantity having both magnitude and direction. Whereit is referred to as a signed quantity, a flow rate may be nominallypositive for the inspiratory portion of a breathing cycle of a patient,and hence negative for the expiratory portion of the breathing cycle ofa patient. Flow rate will be given the symbol Q. ‘Flow rate’ issometimes shortened to simply ‘flow’. Total flow rate, Qt, is the flowrate of air leaving the RPT device. Vent flow rate, Qv, is the flow rateof air leaving a vent to allow washout of exhaled gases. Leak flow rate,Ql, is the flow rate of leak from a patient interface system.Respiratory flow rate, Qr, is the flow rate of air that is received intothe patient's respiratory system.

The invention claimed is:
 1. A method for electronic management of sleeprelated information obtained by a sleep related measurement device, themethod comprising: receiving, by one or more processors, sleep datacomprising data from a plurality of sensors; storing, by the one or moreprocessors, the sleep data so as to associate the sleep data with aplurality of sleep sessions; enabling, by the one or more processors, auser to select for download a selected sleep session; generating, by theone or more processors, a plurality of image tiles corresponding to, andsegmenting of, the sleep data of the selected sleep session byconverting the sleep data of the selected sleep session into a part ofthe plurality of image tiles; generating, by the one or more processors,at least one script element indicative of a diagnostic event associatedwith the sleep data, wherein the at least one script element isconfigured to, when displayed to the user, be superimposed onto at leastone of the plurality of image tiles over a portion of sleep datadepicted in the at least one image tile to indicate when the diagnosticevent occurred in connection with the depicted sleep data; andtransmitting, by the one or more processors, the plurality of imagetiles and the at least one script element.
 2. The method of claim 1wherein the plurality of image tiles are transmitted so that at least afirst image tile, from the plurality of image tiles, are capable ofdisplay by a receiving computer, prior to all of the plurality of imagetiles being downloaded.
 3. The method of claim 1, the method furthercomprising automatically scoring, by the one or more processors,diagnostic events, based on the received sleep data.
 4. The method ofclaim 3, wherein transmitting the plurality of image tiles furthercomprises transmitting an event indicator that identifies scoreddiagnostic events associated with the selected sleep session.
 5. Themethod of claim 4, wherein each of the transmitted image tilescorresponds to a time period included in the event indicator.
 6. Themethod of claim 3, wherein the method further comprises generating areport based on at least one of the sleep data and the scored diagnosticevents.
 7. The method of claim 1, wherein the method further comprisesconfiguring the at least one script elements to be manually adjustableby the user.
 8. The method of claim 7, wherein the method furthercomprises receiving data indicative of user adjustments to the at leastone script elements.
 9. The method of claim 8, wherein the methodfurther comprises recalculating, by the one or more processors, thereport, based on the received data indicative of the user adjustments tothe at least one script elements.
 10. A system for electronic managementof sleep related information obtained by a sleep related measurementdevice, the system comprising: a memory for storing sleep datacomprising data from a plurality of sensors; and one or more processorsin connection with the memory, the one or more processors beingconfigured for: storing the sleep data in the memory, so that the storedsleep data is associated with a plurality of sleep sessions; enabling auser to select for download a selected sleep session; generating aplurality of image tiles corresponding to, and segmenting of, the sleepdata of the selected sleep session by converting the sleep data of theselected sleep session into a part of the plurality of image tiles;generating at least one script element indicative of a diagnostic eventassociated with the sleep data, wherein the at least one script elementis configured to, when displayed to the user, be superimposed onto atleast one of the plurality of image tiles over a portion of sleep datadepicted in the at least one image tile to indicate when the diagnosticevent occurred in connection with the depicted sleep data; andtransmitting the plurality of image tiles and the at least one scriptelement.
 11. The system of claim 10 wherein the plurality of image tilesare transmitted so that at least a first image tile, from the pluralityof image tiles, are capable of being displayed to the user prior to allof the plurality of image tiles being transmitted.
 12. The system ofclaim 10, wherein the one or more processors are further configured toautomatically score diagnostic events, based on the received sleep data.13. The system of claim 12, wherein transmitting the plurality of imagetiles further comprises transmitting an event indicator that identifiesscored diagnostic events associated with the selected sleep session. 14.The system of claim 13, wherein each of the transmitted tilescorresponds to a respective time period included in the event indicator.15. The system of claim 11, wherein the one or more processors arefurther configured to generate a report based on the sleep data and/orthe scored diagnostic events.
 16. The system of claim 10, wherein theone or more processors are further arranged to configure the at leastone script elements to be manually adjustable by the user.
 17. Thesystem of claim 16, wherein the one or more processors are furtherconfigured to receive data indicative of user adjustments to the atleast one script elements.
 18. The system of claim 17, wherein the oneor more processors are further configured to recalculate the report,based on the received data indicative of the user adjustments to the atleast one script elements.
 19. The method of claim 1, wherein each imagetile represents sleep data for a time period within the selected sleepsession.
 20. The system of claim 10, wherein each image tile representssleep data for a time period within the selected sleep session.
 21. Themethod of claim 1 wherein the sleep data comprises a plurality of signalchannels, each signal channel associated with a different type of sleepdata, and wherein the generating of the plurality of image tilescomprises converting sleep data from the plurality of signal channelsinto bitmap image tiles.
 22. The system of claim 10 wherein the sleepdata comprises a plurality of signal channels, each signal channelassociated with a different type of sleep data, and wherein thegenerating of the plurality of image tiles comprises converting sleepdata from the plurality of signal channels into bitmap image tiles.